Paper Abstract and Keywords |
Presentation |
2013-07-19 09:30
A neuroscientific explanation for the brain's memory system with the cocktail party effect by the iterative learning method
-- A Hebb's learning model for the network system of neurons with the analog-digital operating characteristics -- Miyuki Seino (Seino Information System) NC2013-15 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This paper describes the cocktail party effect as a phenomenon of the brain’s active memory system by iterative learning mechanism. The quantity of memory for an object is increased with the number of times of learning the features in the object, along the sigmoid learning curve. The transient noise during learning may not be memorized because of the fewer number of learning. Indeed, the iterative learning mechanism is an automatic valuation system as well as an automatic noise reduction system for memorizing. The memory model is statistical as well as based on Hebb’s learning model on the neuron-synapse level. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
cocktail party effect / iterative learning mechanism / active memory / noise reduction / evaluation / EPSP / IPSP / memory on link |
Reference Info. |
IEICE Tech. Rep., vol. 113, no. 148, NC2013-15, pp. 1-6, July 2013. |
Paper # |
NC2013-15 |
Date of Issue |
2013-07-12 (NC) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NC2013-15 |
Conference Information |
Committee |
NC MBE |
Conference Date |
2013-07-19 - 2013-07-20 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
The University of Tokushima |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
ME, general |
Paper Information |
Registration To |
NC |
Conference Code |
2013-07-NC-MBE |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A neuroscientific explanation for the brain's memory system with the cocktail party effect by the iterative learning method |
Sub Title (in English) |
A Hebb's learning model for the network system of neurons with the analog-digital operating characteristics |
Keyword(1) |
cocktail party effect |
Keyword(2) |
iterative learning mechanism |
Keyword(3) |
active memory |
Keyword(4) |
noise reduction |
Keyword(5) |
evaluation |
Keyword(6) |
EPSP |
Keyword(7) |
IPSP |
Keyword(8) |
memory on link |
1st Author's Name |
Miyuki Seino |
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Seino Information System (Seino Information System) |
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Speaker |
Author-1 |
Date Time |
2013-07-19 09:30:00 |
Presentation Time |
25 minutes |
Registration for |
NC |
Paper # |
NC2013-15 |
Volume (vol) |
vol.113 |
Number (no) |
no.148 |
Page |
pp.1-6 |
#Pages |
6 |
Date of Issue |
2013-07-12 (NC) |